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Article
Discriminative feature representation for Noisy image quality assessment
Blind image quality assessment (BIQA) is one of the most challenging and difficult tasks in the field of IQA. Given that sparse representation through dictionary learning can learn the image feature well, this...
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Chapter and Conference Paper
Longitudinal Detection of Diabetic Retinopathy Early Severity Grade Changes Using Deep Learning
Longitudinal medical image analysis is crucial for identifying the unobvious emergence and evolution of early lesions, towards earlier and better patient-specific pathology management. However, traditional com...
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Chapter and Conference Paper
Deep Active Learning for Dual-View Mammogram Analysis
Supervised deep learning on medical imaging requires massive manual annotations, which are expertise-needed and time-consuming to perform. Active learning aims at reducing annotation efforts by adaptively sele...
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Chapter and Conference Paper
A Hybrid Cloud Deployment Architecture for Privacy-Preserving Collaborative Genome-Wide Association Studies
The increasing availability of sequenced human genomes is enabling health professionals and genomics researchers to well understand the implication of genetic variants in the development of common diseases, no...
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Article
Automatic source scanner identification using 1D convolutional neural network
In this digital world, digitized documents can be considered original or a piece of evidence; checking the authenticity of any suspicious image has become an unavoidable concern to preserve the trust in its le...
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Chapter and Conference Paper
Robust and Imperceptible Watermarking Scheme for GWAS Data Traceability
This paper proposes the first robust watermarking method of outsourced or shared genomic data in the context of genome-wide association studies (GWAS) with the primary purpose of identifying the individual or ...
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Article
Multipath neural networks for anomaly detection in cyber-physical systems
An Intrusion Detection System (IDS) is a core element for securing critical systems. An IDS can use signatures of known attacks, or an anomaly detection model for detecting unknown attacks. Attacking an IDS is...
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Article
Open AccessAutomatic de-identification of French electronic health records: a cost-effective approach exploiting distant supervision and deep learning models
Electronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data presents security and confidentiality challenges. De-identification is ther...
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Article
Global texture sensitive convolutional transformer for medical image steganalysis
Steganography is often used by hackers or illegal organizations as a vehicle for information interception of medical images. Exchanged between PACS or communicated during telemedicine sessions, images are modi...
